In this project, we will investigate the effects of neighborhood social context on biomarkers of stress and health for children and adults of all ages. We will use new data from the Los Angeles Family and Neighborhood Survey (L.A.FANS), whose design remedies many of the problems that have limited previous research on neighborhood effects, by collecting longitudinal data on neighborhoods, families, adults, and children, and on residential choice and neighborhood change. The first wave (L.A.FANS-1), completed in January 2002, interviewed adults and children living in 3,090 households in a diverse stratified probability sample of 65 neighborhoods throughout Los Angeles County. The second wave (L.A.FANS-2), planned for 2005-2006, is being funded by NICHD and NIA and includes the collection of biomarkers of stress and health for adults in the sample, data on adults and on children and their caregivers, as well as information on neighborhood social and physical conditions. As part of this project (L.A.FANS-2/Health), fieldwork will be undertaken to collect similar biomarkers of stress and health for all children in the sample. Data collection will be conducted simultaneously with the main L.A.FANS-2 survey, which will promote efficiency and reduce costs. The specific aims of this project are to: (1) collect physiological markers of stress, disease, and health, including obesity, cortisol (a stress hormone), blood pressure, C-reactive protein (a marker of acute inflammation), Epstein-Barr virus antibodies (a marker of immune function), cholesterol, diabetes, and pulmonary function for all children in L.A.FANS-2; and (2) investigate the effects of social context and family environment on health status for adults and children, focusing on physiological markers of stress and health across the life course. Extensive information will be available from the L.A.FANS database on respondents' social environment as well as confounding factors such as neighborhood choice, residential mobility, migration, and neighborhood change. We will use multilevel statistical models to control for unobserved heterogeneity at the individual, family, and neighborhood levels and will employ extensions of these models, as well as fixed effects models, to tackle issues of endogeneity using longitudinal data and data on matched respondents from the same family.